EMPAC is all about bringing together the best thinking and insights in order to improve policing and better protect the public. We are interested in driving accelerated innovation and enterprise in order to tackle crime.
We are particularly interested in cross border, shared policing problems, for example to better understand how vulnerabilities in communities could be reduced in order to make them less appealing to organised crime groups (OCGs).
OCGs exploit vulnerability as part of their business model, so a better understanding of how this operates is an opportunity to cut crime by protecting communities.
Research is about finding out what we didn’t know before, in order to enhance our decision making capability; there are different sorts of research that can complement each other. Some forms of analysis tend to be confirmatory in spotting patterns and correlations. Other aspects – such as exploratory research – tend to look forward to possible emergent trends and identifying creative opportunities to get upstream.
One way we are seeking to implement more blended analysis and exploratory research is to examine community vulnerabilities as a way of understanding how, where and why OCGs target.
In particular, we are interested in understanding why some ‘cold spots’ appear to be less affected by SOC, in order to identify possible transferable traits that could be utilised in hot spot areas. By drawing on some multiple sources of data that characterise communities and use the mapping insights in creative application opportunities we can explore how hotspot areas being targeted by OCGs can be supported to become more resilience and better protected.
The notion of a cold spot is an opportunity for us in that, in medical analogy terms, whilst we may spot a disease in someone who is affected through their symptoms, we may learn more about cures and indeed prevention by examining why another might not be infected.
In other words, problem solving might sometimes focus just on the symptoms of an issue, rather than looking at solution spotting by starting at the other end – why does a place not have a problem – to learn from existent positive exemplars. We would like to complement that vast literature out there on crime – as a negative – with understanding the non crime phenomena more – as a positive – to learn from. So we’re interested here in doing the converse to crime mapping and analysis – more of a non-crime (a kind of tranquility index) mapping and analysis: so one can inform the other.
Cold spots can be flexibly explored using multiple avenues of open source data, using Python, R, VBA or matlab to model data to carry out principal component analysis to identify variables. It is anticipated that time series analysis, principal component analysis, clustering technique could be beneficial in making sense of multiple forms of data.
Open source data is available at numerous sites including:-
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The opportunity here is to identify trends by overlaying multiple data sets to give a rich picture of cold spots. Then, to explore and cross compare how those identified trends relate to hot spot areas.
The overall purpose is to help build and strengthen community resilience, making it more inhospitable for organised crime to profit from it.
We’re not short of data in this day and age, but it can be a challenge to make sense of the amount and variety of data out here – the opportunity here is to make sense of data and identify some trends that have been perhaps hiding in open view. Lists of data are one thing to describe a pattern but we’re keen to explain and understand why things happen.
Reporting back on identified trends offers an opportunity to help shape and influence policy and practice, and ultimately make some people’s lives safer and that’s a difference worth making!